Semantic Contours in Tracks Based on Emotional Tags

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2009

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Outlining a high level cognitive approach to how we select media based on affective user preferences, we model the latent semantics of lyrics as patterns of emotional components. Using a selection of affective last.fm tags as top-down emotional buoys, we apply LSA latent semantic analysis to bottom-up represent the correlation of terms and song lyrics in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, by comparing them against last.fm tag clouds describing the corresponding songs, we propose that it might be feasible to automatically generate affective user preferences based on song lyrics.
Original languageEnglish
Title of host publicationComputer Music Modeling and Retrieval. : Genesis of Meaning in Sound and Music
Number of pages285
VolumeVolume 5493/2010
PublisherSpringer
Publication date2009
Edition1st
Pages45-66
ISBN (print)978-3-642-02517-4
DOIs
StatePublished

Conference

ConferenceComputer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music
Number5th
CityCopenhagen, Denmark,
Period01/01/08 → …
NameLecture Notes in Computer Science: Information Systems and Applications
Number5493
ISSN (Print)0302-9743
CitationsWeb of Science® Times Cited: No match on DOI
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